• Murat ŞİMŞEK Electric and Electronic Engineering, Kirikkale University
  • Volkan ATEŞ Electric and Electronic Engineering, Kirikkale University
  • Murat LÜY Electric and Electronic Engineering, Kirikkale University
Keywords: SAR image, edge detection, ant colony optimization, ant colony algorithm, heuristic optimization.


Object/Target detection is difficult to process due to speckles in SAR images, which provide high radiometric and geometric resolution independent of all atmospheric conditions. By using edge detection method which extracts important information in the image, it is possible to obtain higher accuracy and less processing SAR image for target detection by eliminating these speckles. The ant colony algorithm, which is one of the heuristic optimization methods, is an algorithm based on mathematical models of real ant colony behaviors. In image processing area, Ant Colony Optimization (ACO) provides an effective contribution in some methods such as object/target detection in specific images by using edge detection technique. We aim to eliminate the speckles that make difficult for target detection in SAR images by using Edge Detection based on Ant Colony Optimization, which is an effective optimization method.



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How to Cite
ŞİMŞEK, M., ATEŞ, V., & LÜY, M. (2018). EDGE DETECTION BASED ON ANT COLONY OPTIMIZATION IN SAR IMAGES. International Journal of Scientific Research in Information Systems and Engineering (IJSRISE), 4(1), 37-41. Retrieved from http://ijsrise.com/index.php/IJSRISE/article/view/7
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